Plan publishable constraint-based metabolic modelling studies when the user has a broad biological or metabolic-engineering topic but no concrete dataset, organism, model, or hypothesis. Selects feasible BiGG/COBRA models, objectives, perturbations, analyses, metrics, figures, and risk controls before FBA code is generated.
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Use this skill before gsmm-builder, fba-simulator, and flux-analyzer when
the project starts from a broad prompt such as "do a metabolic flux analysis
paper" or "find a publishable idea in microbial metabolism".
The goal is to turn a vague topic into a concrete, executable, paper-shaped study plan:
organism + model + condition + perturbation + metric + figure set + claimThis is the MFA analogue of choosing a collider process and parameter scan before generating events.
Extract or infer the following:
| Field | Examples |
|---|---|
| Biological scope | microbial metabolism, cancer metabolism, yeast fermentation, tuberculosis |
| Organism | E. coli, S. cerevisiae, human Recon3D, M. tuberculosis |
| Model source | BiGG ID, local SBML/JSON, manually constructed toy model |
| Objective | biomass, product secretion, ATP maintenance, dual objective |
| Condition | aerobic, anaerobic, carbon source, nutrient limitation |
| Perturbation | gene knockout, reaction knockout, medium swap, oxygen sweep |
| Target output | growth, product yield, essential genes, secretion profile |
| Paper type | mechanism hypothesis, metabolic engineering strategy, benchmark, reproduction |
If the user provides no organism, start with one of these low-risk defaults:
| Default | Model | Why |
|---|---|---|
| E. coli K-12 | iJO1366 or core model | Fast, well curated, standard for FBA papers |
| S. cerevisiae | iMM904 | Fermentation and product-yield studies |
| Human metabolism | Recon3D | Disease metabolism, but larger and harder |
| M. tuberculosis | iNJ661 | Essentiality and drug-target hypotheses |
Prefer E. coli for fully autonomous first runs because it is fast and interpretable.
Use when the topic mentions metabolic engineering, bio-production, yield, or fermentation.
Plan:
Required metrics:
Paper claim format:
Constraint-based screening predicts that perturbing
<pathway>improves<product>secretion while preserving<growth_fraction>of WT growth.
Use when the topic mentions adaptation, nutrient limitation, aerobic/anaerobic growth, diauxie, or environmental stress.
Plan:
Required metrics:
flux_maximumPaper claim format:
A two-axis nutrient envelope reveals distinct feasible metabolic regimes and predicts condition-specific secretion shifts.
Use when the topic mentions antimicrobial targets, cancer metabolism, essential genes, or robustness.
Plan:
Required metrics:
Paper claim format:
FBA essentiality analysis prioritises
<subsystem>as a condition-dependent vulnerability under<medium>.
Use when the topic is methodological or AutoResearchClaw asks for a benchmark.
Plan:
Required metrics:
Paper claim format:
A standardised COBRApy protocol improves reproducibility of metabolic phenotype predictions across models and media.
Before committing to a study, score candidate ideas from 1-5:
| Criterion | Reject if |
|---|---|
| Model availability | no BiGG/SBML/JSON model or no clear toy model |
| Runtime | requires exhaustive double knockouts on large models |
| Interpretability | no identifiable pathway/subsystem or biological claim |
| Output richness | fewer than 3 meaningful figures/tables |
| Reproducibility | depends on undocumented proprietary data |
Proceed only if total score is at least 18/25. Otherwise choose a simpler organism, narrower product, or smaller perturbation space.
Write a study_card.md before code generation:
# Metabolic Study Card
## Research Question
One sentence.
## Hypothesis
One falsifiable claim.
## Model
- Organism:
- Model ID / source:
- Objective reaction:
## Conditions
- Medium:
- Carbon source:
- Oxygen bounds:
## Analyses
- FBA:
- pFBA:
- FVA:
- Knockout screen:
- Production envelope:
## Metrics
- Growth rate:
- Product flux:
- Yield:
- Essentiality:
- Robustness:
## Figures
1. WT vs perturbation flux summary
2. Product yield ranking
3. Production envelope / phase map
4. Essentiality or subsystem enrichment plot
## Risks
- Model curation risk:
- Solver/runtime risk:
- Biological interpretation risk:When this skill is matched in AutoResearchClaw:
hypothesis_gen, propose hypotheses tied to a named model and analysis.experiment_design, include a concrete model ID, objective reaction,
perturbation set, and metrics.code_generation, generate a self-contained COBRApy script that can run
either on a local model file or on a minimal fallback toy model if the full
model is unavailable.result_analysis, do not overclaim experimental validation. Phrase results
as model-based predictions.If the user has no idea, start with:
Predict robust reaction knockout strategies for succinate overproduction in
E. coli using COBRApy FBA, pFBA, FVA, and oxygen/glucose production envelopes.This topic is computationally feasible, uses a standard organism, produces multiple figures, and has an interpretable metabolic-engineering narrative.
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